AGIS Modernizes Order Planning and Cuts Planning Time by 75% with SAP BTP

Middle East based flat steel producer, Al Ghurair Iron and Steel LLC (AGIS), has modernized production planning and execution by implementing an SAP BTP and SAP Business AI solution integrated with SAP Cloud ERP Private. Working with Deloitte, AGIS digitized about 90% of its end-to-end make-to-order process and automated 300+ material and process calculations.  

The company operates in one of the most demanding segments of the metals value chain, where product customization, short lead times, and tight margins are the norm. To support its industrial and sustainability goals, AGIS needed to break down operational silos across planning, production, quality, and sustainability reporting.  

AGIS and Deloitte deployed an extensible AI-enabled architecture that automated hundreds of calculations, aligned production to highly granular customer requirements, and improved transparency into material traceability. 

Digitizing Complex Planning Logic  

At AGIS, production planning and execution were previously managed through offline, Excel based processes across a 500,000 metric ton operation. Frequent changes in customer specifications, raw material constraints, and sales volumes required constant manual intervention, while execution teams handled multiple redundant system steps. This fragmented approach limited scalability, slowed response times, and made it difficult to consistently meet production targets. 

The company also had to consider the challenge of operating in a manufacturing environment shaped by unpredictable supply chains, geopolitical shifts, and mounting cost pressures. Thus, implementing a solution required balancing the need for robust long‑term planning with the flexibility to respond quickly to changes in materials, orders, and production capacity.  

Increased Visibility Through an AI Driven Manufacturing Core 

​AGIS standardized core operations on SAP Cloud ERP Private then used SAP Business Technology Platform (SAP BTP) to handle steel-specific planning and execution logic without over-customizing the ERP core.  

On top of this core, AGIS implemented SAP BTP services and SAP Build solutions to orchestrate production planning and execution workflows that reflect real world plant constraints. SAP Build Work Zone and related low-code capabilities provided planners, production supervisors, and commercial teams with unified workspaces to access AI recommendations, production statuses, and exception alerts in context. This helped AGIS move away from Excel-driven planning and digitize about 90% of the end-to-end make-to-order process.  

As a result, the steel producer reported order planning time dropping to less than five minutes, from 15-20 minutes. The unified operator experience delivered through SAP Build Work Zone dashboards reduced batch execution time to under three minutes from 8-10 minutes. 

​​ By digitizing about 90% of previously manual processes, AGIS built a stronger data foundation for operational visibility and real-time sustainability reporting. AGIS says integrations pull critical ESG (Environmental, Social, and Governance) reporting data from the MES (Manufacturing Execution System) machinery data module to support that reporting. 

​What This Means for SAPinsiders 

Clean-core design is becoming the practical starting point for AI-enabled manufacturing. Keeping SAP S/4HANA Cloud standardized while moving complex plant- and industry-specific logic to SAP BTP helps teams innovate faster without turning the ERP core into a customization bottleneck. In SAPinsider’s 2025 S/4HANA migration benchmark survey, 43% of respondents said they are focusing on modernizing or eliminating custom processes – reinforcing the move towards clean-core discipline as a practical requirement. 

AI-driven planning works best when it reflects real plant constraints, not just better algorithms. At AGIS, the solution automates 300+ calculations and uses 90+ attribute variations to recommend raw-material batches and support planning decisions. 

Standardized, real-time data can support both efficiency work and sustainability reporting. When operational data is digitized and connected through the platform layer, it becomes easier to speed up planning, reduce manual handoffs, and feed sustainability reporting from the same underlying process data – an area where many manufacturers still have gaps.